20 April 2010 Near-infrared hyperspectral imaging for quality analysis of agricultural and food products
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Abstract
Agricultural and food processing industries are always looking to implement real-time quality monitoring techniques as a part of good manufacturing practices (GMPs) to ensure high-quality and safety of their products. Near-infrared (NIR) hyperspectral imaging is gaining popularity as a powerful non-destructive tool for quality analysis of several agricultural and food products. This technique has the ability to analyse spectral data in a spatially resolved manner (i.e., each pixel in the image has its own spectrum) by applying both conventional image processing and chemometric tools used in spectral analyses. Hyperspectral imaging technique has demonstrated potential in detecting defects and contaminants in meats, fruits, cereals, and processed food products. This paper discusses the methodology of hyperspectral imaging in terms of hardware, software, calibration, data acquisition and compression, and development of prediction and classification algorithms and it presents a thorough review of the current applications of hyperspectral imaging in the analyses of agricultural and food products.
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C. B. Singh, C. B. Singh, D. S. Jayas, D. S. Jayas, J. Paliwal, J. Paliwal, N. D. G. White, N. D. G. White, } "Near-infrared hyperspectral imaging for quality analysis of agricultural and food products", Proc. SPIE 7676, Sensing for Agriculture and Food Quality and Safety II, 767603 (20 April 2010); doi: 10.1117/12.850371; https://doi.org/10.1117/12.850371
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